Computing and networking technologies have transformed many important aspects of everyday life. Computers have become a household staple instead of a luxury, educational tool or entertainment center, and provide users with a tool to manage and forecast finances, control household operations like heating, cooling, lighting and security, and store records and images in a permanent and reliable medium. Networking technologies like the Internet provide users with virtually unlimited access to remote systems, information and associated applications.
As computing and networking technologies become robust, secure and reliable, more consumers, wholesalers, retailers, entrepreneurs, educational institutions and the like are shifting paradigms and employing networks, such as the Internet, to perform business instead of the traditional means. For example, many businesses and consumers are providing web sites or on-line services. For example, today a consumer can access his/her account via the Internet and perform a growing number of available transactions such as balance inquiries, funds transfers and bill payment.
Typically, a network session includes a user interfacing with a client application to interact with a server that stores information in a database that is accessible to the client application. For example, a stock market web site can provide the user with tools for retrieving stock quotes and purchasing stock. The user can type in a stock symbol and request a stock quote by performing a mouse click to activate a query. The client application queries a database table of stocks and returns a stock quote.
A shortcoming of computing and networking technologies is the limited bandwidth. A user consumes a portion of the bandwidth whereby the portion consumed is not available to other users. Therefore, as more and more users employ a network, the available bandwidth decreases which can reduce response time and performance. Another shortcoming of computing and networking technologies is the limited available data transfer rates relative to the quantity of data available. For example, requests that retrieve large amounts of data (e.g., distributed across various servers) can be time intensive, which can diminish performance also.
Thus, Business Intelligence (BI) solutions were developed to aid in accessing information about large databases. Most businesses in recent times have migrated to relational type databases. Data warehouses were developed to store tactical information to answer the “who” and “what” questions about the stored data related to previous events. However, this proved limiting due to the fact that data warehouses only have the capability of retrieving historical data. Therefore, on-line analytical processing (OLAP) systems were developed to not only answer the “who” and “what”, but also the “what if” and “why” of the data. OLAP systems are multidimensional views of aggregate data that allow analysts, business managers, and executives to gain insight into the information through a quick, reliable, interactive process.
Analysis tools, including OLAP tools, help to reduce the access times to extreme amounts of data. By utilizing these tools, a user can ask general questions or “queries” about the data rather than retrieve all the data verbatim. Thus, “data about data” or metadata helps expedite the query process and reduce the required network bandwidth. However, as is typical in a business environment, what was fast yesterday is considered slow by today's standard. There is always an increasing demand for faster information delivery, in spite of the exponentially expanding sizes of data stores.